Graph-based models are popular for many NLP tasks as they work on non-linear structures. [1]} proposed a graph-based model for cross-sentence relation extraction. They built a graph from the sentences where every word is considered as a node in the graph. Edges are created based on the adjacency of the words, dependency tree relations, and discourse relations. They extract all the paths from the graph starting from entity 1 to entity 2. Each path is represented by features such as lexical tokens, the lemma of the tokens, POS tags, etc. They use all the path features to find the relation between the two entities.
